11,930 research outputs found
Structural graph matching using the EM algorithm and singular value decomposition
This paper describes an efficient algorithm for inexact graph matching. The method is purely structural, that is, it uses only the edge or connectivity structure of the graph and does not draw on node or edge attributes. We make two contributions: 1) commencing from a probability distribution for matching errors, we show how the problem of graph matching can be posed as maximum-likelihood estimation using the apparatus of the EM algorithm; and 2) we cast the recovery of correspondence matches between the graph nodes in a matrix framework. This allows one to efficiently recover correspondence matches using the singular value decomposition. We experiment with the method on both real-world and synthetic data. Here, we demonstrate that the method offers comparable performance to more computationally demanding method
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Design for Additive Manufacturing: A Method to Explore Unexplored Regions of the Design Space
Additive Manufacturing (AM) technologies enable the fabrication of parts and devices that
are geometrically complex, have graded material compositions, and can be customized. To take
advantage of these capabilities, it is important to assist designers in exploring unexplored regions
of design spaces. We present a Design for Additive Manufacturing (DFAM) method that
encompasses conceptual design, process selection, later design stages, and design for
manufacturing. The method is based on the process-structure-property-behavior model that is
common in the materials design literature. A prototype CAD system is presented that embodies
the method. Manufacturable ELements (MELs) are proposed as an intermediate representation
for supporting the manufacturing related aspects of the method. Examples of cellular materials
are used to illustrate the DFAM method.Mechanical Engineerin
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